About Wipro:
Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients' most complex digital transformation needs. We leverage our holistic portfolio of capabilities in consulting, design, engineering, operations, and emerging technologies to help clients realize their boldest ambitions and build future-ready, sustainable businesses. A company recognized globally for its comprehensive portfolio of services, strong commitment to sustainability and good corporate citizenship, we have over 250,000 dedicated employees serving clients across 66 countries. We deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world.
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- A PROUD HISTORY OF OVER 75 YEARS
- FY22 REVENUE 11.2 BN USD
- WE'RE PRESENT IN 66 COUNTRIES
- OVER 1,400 ACTIVE GLOBAL CLIENTS
Role: ML Ops Test Engineer
Location : Pittsburgh , PA ( Hybrid Role )
Job Type - Full Time Position
Position Overview: An ML Ops Test Engineer is responsible for ensuring the reliability, scalability, and performance of machine learning models in production. This role involves developing and executing comprehensive tests, monitoring model performance, and collaborating with data scientists and software engineers to maintain robust ML systems.
Key Responsibilities:
- Develop and Execute Tests: Design and implement test cases to evaluate the performance, robustness, and reliability of ML models.
- Statistical Analysis: Perform statistical analysis and fine-tuning using test results to improve model accuracy and efficiency.
- Model Monitoring: Continuously monitor the health and performance of deployed models, identifying and addressing issues proactively.
- Collaboration: Work closely with data scientists, software engineers, and DevOps teams to integrate testing processes into the ML lifecycle.
- Automation: Develop and maintain automated testing frameworks and CI/CD pipelines for ML models.
- Documentation: Document test plans, procedures, and results to ensure transparency and reproducibility.
- Stay Updated: Keep abreast of the latest developments in ML, MLOps, and testing methodologies.
- Programming Languages: Proficiency in Python, Java, or Scala.
- Machine Learning Frameworks: Experience with TensorFlow, PyTorch, scikit-learn, or Keras.
- Data Engineering: Knowledge of data pipelines, data processing, and storage solutions like Hadoop, Spark, and Kafka.
- Cloud Computing: Familiarity with cloud platforms such as Azure.
- Containerization and Orchestration: Expertise in Docker and Kubernetes.
- Version Control: Proficiency with Git and CI/CD tools.
- Analytical Skills: Strong analytical and problem-solving skills to interpret test results and improve model performance.
- Experience: Previous experience in MLOps, software testing, or a related field.
- Certifications: Relevant certifications such as Azure AI Engineer Associate.
- Communication: Excellent verbal and written communication skills to collaborate effectively with cross-functional teams.
- Attention to Detail: Meticulous attention to detail to ensure the accuracy and reliability of test results.
- Adaptability: Ability to adapt to rapidly changing technologies and methodologies in the ML and MLOps landscape.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, caste, creed, religion, gender, marital status, age, ethnic and national origin, gender identity, gender expression, sexual orientation, political orientation, disability status, protected veteran status, or any other characteristic protected by law. Any complaints or concerns regarding unethical/unfair hiring practices should be directed to our Ombuds Group.
AI/ML App Testing